Back in the time, in late 1990’s , the Market was over flooded by actions and participation of Hedge Funds . They were very successful in attracting billions of dollars in Investment, and were stronger than most of the World Central Banks.
This is the story of one of them – Namely LTCM
LTCM was formed in 1994 and was founded by renowned Salomon Brothers bond trader John Meriwether, along with Nobel-prize winner Myron Scholes.
For the first time in a history of the market, one Fund was led by a Scientist, a Nobel-prize winner…so what can go wrong ???
Well, everything – and this is what I am going to talk about.
I am going to skip on the details of their day by day actions, and try to give you some clear points.
LTCM started with just over $1 billion in initial assets and focused on bond trading. The trading strategy of the fund was to make convergence trades, which involve taking advantage of arbitrage opportunities between securities.
So more or less kind of a Day trading, that would stretch for longer periods of time, in case they were right .
Mistake number 1 – never, ever change your trading plan on the run.
Due to the small spread in arbitrage opportunities, LTCM had to leverage itself highly to make money. At the fund’s height in 1998, LTCM had approximately $5 billion in assets, controlled over $100 billion, and had derivative positions whose total worth was over $1 trillion. At the time, LTCM also had borrowed more than $155 billion in assets.
Mistake number 2 – never, ever leverage yourself so much, that one wrong decision will wipe out your whole Margin
August 1998, LTCM was holding a significant position in Russian government bonds
LTCM’s highly leveraged nature, coupled with a financial crisis in Russia, led the hedge fund to sustain massive losses and be in danger of defaulting on its own loans. This made it difficult for LTCM to cut its losses in its positions. LTCM held huge positions, totalling roughly 5% of the total global fixed-income market, and had borrowed massive amounts of money to finance these leveraged trades.
Mistake number 3 – If in Trouble, than you Double mantra – Never, ever ever add to the losing position.
When the losses approached $4 billion, the federal government of the United States feared that the imminent collapse of LTCM would precipitate a larger financial crisis and orchestrated a bailout to calm the markets. A $3.625-billion loan fund was created, which enabled LTCM to survive the market volatility and liquidate in an orderly manner in early 2000.
So, End of the Story…but is it ???
Nah…I have to point few more important details.
How can a Fund led by a Nobel Prize winner get trashed so much and so fast ??
Well, they had several Critical mistakes from early on (probably from the start )
- Fund relied heavily on their proprietary System, run by their Computer systems that despite hundreds of millions of dollars Daily losses were recommending holding on the Positions.
That is what happens when you fully rely on AI.
- Nobel Prize winner – The Scientist – obviously didn’t do his job right Back testing – Not enough data to support the pattern recognition.
- The nature of any Fund – to make as much profits as possible in as short time as possible.
So, they did make every single mistake possible in trading, but if they just controlled one of them – particularly Risk Management, they would most probably still be with us today – if they just traded with lower leverage ( Greed is a killer ) , or had Stops in place to avoid being wiped up entirely ( Fear of being wrong ) and jumped on the wagon after that killing correction , or never Doubled their position trying to scale their entry points – get a better average price – most probably they would avoid their demise.
So what can you learn from this story? Everything ! Be it a Hedge Fund trading in trillions or modest yourself trading in maybe tens of thousands , if you follow the rules of the engagement and never break them , your chances to survive to trade another day are growing exponentially .
I hope this brutal story can help you understand how it really works.
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